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Please use this identifier to cite or link to this item: http://hdl.handle.net/10651/11339

Title: Weighted tardiness minimization in job shops with setup times by hybrid genetic algorithm
Author(s): González Fernández, Miguel Ángel
Rodríguez Vela, María del Camino
Varela Arias, José Ramiro
Issue date: 2011
Publisher: Springer
Publisher version: http://dx.doi.org/10.1007/978-3-642-25274-7_37
Citation: Advances in Artificial Intelligence, p. 363-372 (2011); doi:10.1007/978-3-642-25274-7_37
Series/Report no.: Lecture Notes in Computer Science;7023
Format extent: p. 363-372
Abstract: In this paper we confront the weighted tardiness minimization in the job shop scheduling problem with sequence-dependent setup times. We start by extending an existing disjunctive graph model used for makespan minimization to represent the weighted tardiness problem. Using this representation, we adapt a local search neighborhood originally defined for makespan minimization. The proposed neighborhood structure is used in a genetic algorithm hybridized with a simple tabu search method. This algorithm is quite competitive with state-of-the-art methods in solving problem instances from several datasets of both classical JSP and JSP with setup times
Description: Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2011 (14th. 2011. La Laguna, España)
URI: http://hdl.handle.net/10651/11339
ISBN: 978-3-642-25273-0
ISSN: 0302-9743
Local identifier: 20111628
Sponsored: This research has been supported by the Spanish Ministry of Science and Innovation under research project MICINN-FEDER TIN2010- 20976-C02-02 and by the Principality of Asturias under grant FICYT-BP07-109
Project id.: MICINN-FEDER/TIN2010-20976-C02-02
FICYT/BP07-109
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